AI Ethics Practice Areas
Tags: Frameworks
TL;DR —
- 18 practice areas span strategy to operations, forming a concrete checklist for ethical AI delivery.
- Covers procurement ethics, data quality, privacy-by-design, model testing, deployment safeguards, and ongoing monitoring.
- Referenced directly by AI Assessment questions.
Why it matters for HK marketers: It’s a ready-made QA and governance checklist for AI-infused campaigns, martech tooling, and vendor procurement.
Practice areas by lifecycle stage
Project Strategy
- Organisation Strategy, Internal Policies & Practices — Ensure explainability and ethical decision-making are embedded.
- Industry Standards & Regulations — Assess alignment with relevant laws and standards.
Project Planning
- Portfolio Management — Confirm AI projects address business objectives and value.
- Project Oversight & Delivery Approach — Quality control across the project per the Project Management Plan.
Project Ecosystem
- Technology Roadmap for AI & Data Usage — Plan what to adopt and when.
- Procuring AI Services — Evaluate third-party products and data with ethical considerations.
Project Development
- Business & Data Understanding — Define objectives; balance benefits and risks.
- Solution Design — Assess model suitability and level of human intervention.
- Data Extraction — Assure data quality, validity, reliability, and consistency.
- Pre-processing — Protect sensitive data; prevent leakage and privacy/security breaches.
- Model Building — Mitigate errors (e.g., wrong assumptions, overfitting, adversarial attacks).
System Deployment
- Model Integration & Impact — Verification, validation, and testing to ensure requirements are met.
- Transition & Execution — Pre-plan mitigations assuming failure scenarios.
- Ongoing Monitoring — Feedback to maintain performance and robustness.
- Evaluation & Check-in — Ensure traceability, repeatability, and reproducibility.
System Operation & Monitoring
- Data & Model Performance Monitoring — Continuous monitoring/review for drift and relevance.
- Operational Support — Maintain consistent, reliable, robust performance.
- Continuous Review/Compliance — Monitor for new/revised laws and regulations; manage escalation.
18 practice areas across 6 lifecycle stages.
So what for marketers
Turn these 18 areas into your AI delivery checklist and vendor RFP criteria; require suppliers to evidence how they meet each practice before onboarding.
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